Method for calibrating a non-contact sensor using a robot

• US 20060271332A1
• Filed: 03/24/2006
• Published: 11/30/2006
• Est. Priority Date: 05/18/2005
• Status: Abandoned Application

• Current Assignee: Perceptron Incorporated (Atlas Copco AB)
• Original Assignee: Perceptron Incorporated (Atlas Copco AB)
• Inventors: Loferer, Hannes
• Application Number:
  US11/389,600
• Publication Number:
  US 20060271332A1
• Time in Patent Office: Days
• US Class Current: 702/150
• CPC Class Codes: G01B 21/042 Calibration or calibration artifacts G01B3/30, G01B9/02072 take precedence

Abstract

A method is provided for calibrating a non-contact sensor with respect to an external reference frame through the use of a robot associated with a manufacturing workstation. The method includes: identifying a target associated with the robot; capturing image data of the target by the non-contact sensor as the target is moved amongst six different measurement positions within a field of view of the non-contact sensor; capturing positional data for the robot as reported by the robot at the measurement positions, where the positional data for the robot is reported in the external reference frame; determining positional data for the target based in part on the image data, wherein the positional data is defined in a sensor reference frame associated with the non-contact sensor; and determining a transform between the sensor reference frame and the external reference frame based on the positional data for the target and the positional data for the robot.

Claims

1. A method for calibrating a non-contact sensor with respect to an external reference frame through the use of a robot associated with a manufacturing workstation, comprising:

identifying a target associated with the robot;

capturing image data of the target by the non-contact sensor as the target is moved amongst six different measurement positions within a field of view of the non-contact sensor;

capturing positional data for the robot as reported by the robot at the measurement positions, where the positional data for the robot is reported in the external reference frame;

determining positional data for the target based in part on the image data, wherein the positional data is defined in a sensor reference frame associated with the non-contact sensor;

determining a transform between the sensor reference frame and the external reference frame based on the positional data for the target and the positional data for the robot.

2. The method of claim 1 further comprises capturing positional data for the target coincidental with capturing position data for the robot.

3. The method of claim 1 further comprises affixing a sphere to the robot to serve as the target for the non-contact sensor.

4. The method of claim 1 further comprises deriving a tool-to-part transform between the positional data reported by the robot and the external reference frame and using the transform to program the robot to report positional data in the external reference frame.

5. The method of claim 1 further comprises determining

determining points on a surface of the sphere in the sensor reference frame using the image data of the target captured by the non-contact sensor;

determining points on a surface of the sphere in the external reference frame;

determining a center of the sphere in the external reference frame; and

subtracting the points on a surface of the sphere from the center of the sphere and equating to a known radius of the sphere.

6. The method of claim 5 wherein determining points on a surface of the sphere in the sensor reference frame further comprises determining a center of an arc formed by the image data and adding a radius measure to the center of the arc.

7. The method of claim 5 further comprises multiplying the points on a surface of the sphere in the sensor reference frame by an unknown transform between the sensor reference frame and the external reference frame;

and multiplying an unknown center of the sphere in a reference frame associated with the tool by the tool-to-part transform.

8. The method of claim 7 further comprises solving for the unknowns using a least squares fit algorithm.

9. The method of claim 5 further comprises computing the transform between the sensor reference frame and the external reference frame in accordance with Eulers rotational theorem.

10. A method for determining a transform between positional data as reported by a robot residing in a manufacturing workstation and an external reference frame, comprising:

affixing a target to the robot in a manner such that position of the target is unknown in a base reference frame of the robot;

moving the target to at least six measurement positions within a field of observation of a target calibration device;

capturing positional data for the target by the target calibration device at each of the measurement positions, wherein the positional data for the target is defined in the external reference frame;

capturing positional data for the robot as reported by the robot at each of the measurement positions, wherein the positional data for the robot is defined in the base reference frame associated with the robot; and

determining a transform between the base reference frame associated with the robot and the external reference frame based on the positional data for the target and the positional data for the robot.

11. The method of claim 10 wherein capturing positional data for the target further comprises placing a retroreflector on a nesting station coupled to the robot and capturing positional data for the retroreflector using a laser tracker.

12. The method of claim 10 further comprises capturing positional data for the target coincidental with capturing positional data for the robot.

13. The method of claim 10 further comprises determining a flange-to-robot transform between an end-effector of the robot and the base reference frame of the robot based in part on the positional data captured by the robot.

14. The method of claim 13 further comprises

defining an unknown position of the target relative to the base reference frame of the robot using the flange-to-robot transform;

defining a mathematical function between the position data for the target as reported by the target calibration device and a product of unknown position of the target relative to the base reference frame of the robot with an unknown transform between the base reference frame of the robot and the external reference frame; and

solving for unknowns of the mathematical function to determine the transform between the base reference frame of the robot and the external reference frame.

15. The method of claim 10 further comprises deriving a tool-to-part transform between a tool configured on the robot and an arbitrary reference frame external to the robot based on the positional data captured by the robot.

16. The method of claim 15 further comprises computing a tool-to-robot transform by multiplying the tool-to-part transform with a part-to-robot transform between the arbitrary reference frame and the base reference frame of the robot, where the part-to-robot transform is given by the robot.

17. The method of claim 16 further comprises computing a flange-to-robot transform between an end-effector of the robot and the base reference frame of the robot by multiplying the tool-to-robot transform with an inverse of a tool-to-flange robot as given by the robot.

18. The method of claim 17 wherein determining a transform further comprises:

minimizing a distance between positional data for the target as defined in the external reference frame and a product of an unknown transform between the base reference frame of the robot and the external reference frame with flange-to-robot transform and with an unknown position of target relative to the end-effector of the robot; and

computing the transform between the base reference frame of the robot and the external reference frame in accordance with Eulers rotational theorem.